Research in the field of computer vision has always focused on the detection of specific targets in an image. Research on the identification of armored vehicles in the battlefield environment, as well as the deployment dynamics, recognition and tracking, precise strike, and so on, are critical military objectives. There are still many difficulties in detecting armored vehicles on the battlefield because of the complication of the environment [1]}, [2]}. Authors in [3]}, [4]} proposed multimodal learning approach in object detection task. We have presented a novel multimodal learning approach in battlefield object detection based on image and audio modality. Figure REF  shows the highlevel overview of the evaluation of TinyM\(^2\) Net in terms of battlefield object detection.
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